SoroushVahidi/scidocs huggingface dataset:
Personalized Reliability Prediction of Web Services
(2013)

Service Oriented Architecture (SOA) is a business-centric IT architectural approach for building distributed systems. Reliability of service-oriented systems heavily depends on the remote Web services as well as the unpredictable Internet connections. Designing efficient and effective reliability prediction approaches of Web services has become an important research issue. In this article, we propose two personalized reliability prediction approaches of Web services, that is, neighborhood-based approach and model-based approach. The neighborhood-based approach employs past failure data of similar neighbors (either service users or Web services) to predict the Web service reliability. On the other hand, the model-based approach fits a factor model based on the available Web service failure data and use this factor model to make further reliability prediction. Extensive experiments are conducted with our real-world Web service datasets, which include about 23 millions invocation results on more than 3,000 real-world Web services. The experimental results show that our proposed reliability prediction approaches obtain better reliability prediction accuracy than other competing approaches.
A Study on the Effective Permittivity of Carbon/PI Honeycomb Composites for Radar Absorbing Design
(2012)

Radar absorbing honeycomb composites with different coating thicknesses are prepared by impregnation of aramid paper frame with solutions containing conductive carbon blacks (non-magnetic) and PI (polyimide). Expressions for the effective permittivity of the composites are studied and validated both in theory and experiment. It is found that a theoretical equivalent panel with given permittivity can be obtained to represent the honeycomb structure in the quasistatic approximation, which provides a feasible way to optimize the design of radar absorbing honeycomb structure by connecting the effective electromagnetic parameters with the unit cell dimensions. The effective permittivity is measured by a network analyzer system in the frequency range of 8-12 GHz and compared with the theoretical result.
SVO: Semidirect Visual Odometry for Monocular and Multicamera Systems
(2017)

Direct methods for visual odometry (VO) have gained popularity for their capability to exploit information from all intensity gradients in the image. However, low computational speed as well as missing guarantees for optimality and consistency are limiting factors of direct methods, in which established feature-based methods succeed instead. Based on these considerations, we propose a semidirect VO (SVO) that uses direct methods to track and triangulate pixels that are characterized by high image gradients, but relies on proven feature-based methods for joint optimization of structure and motion. Together with a robust probabilistic depth estimation algorithm, this enables us to efficiently track pixels lying on weak corners and edges in environments with little or high-frequency texture. We further demonstrate that the algorithm can easily be extended to multiple cameras, to track edges, to include motion priors, and to enable the use of very large field of view cameras, such as fisheye and catadioptric ones. Experimental evaluation on benchmark datasets shows that the algorithm is significantly faster than the state of the art while achieving highly competitive accuracy.
Fuzzy memoization for floating-point multimedia applications
(2005)

Instruction memoization is a promising technique to reduce the power consumption and increase the performance of future low-end/mobile multimedia systems. Power and performance efficiency can be improved by reusing instances of an already executed operation. Unfortunately, this technique may not always be worth the effort due to the power consumption and area impact of the tables required to leverage an adequate level of reuse. In this paper, we introduce and evaluate a novel way of understanding multimedia floating-point operations based on the fuzzy computation paradigm: performance and power consumption can be improved at the cost of small precision losses in computation. By exploiting this implicit characteristic of multimedia applications, we propose a new technique called tolerant memoization. This technique expands the capabilities of classic memoization by associating entries with similar inputs to the same output. We evaluate this new technique by measuring the effect of tolerant memoization for floating-point operations in a low-power multimedia processor and discuss the trade-offs between performance and quality of the media outputs. We report energy improvements of 12 percent for a set of key multimedia applications with small LUT of 6 Kbytes, compared to 3 percent obtained using previously proposed techniques.
Energy-Efficient Multiple-Precision Floating-Point Multiplier for Embedded Applications
(2013)

Floating-point (FP) multipliers are the main energy consumers in many modern embedded digital signal processing (DSP) and multimedia systems. For lossy applications, minimizing the precision of FP multiplication operations under the acceptable accuracy loss is a well-known approach for reducing the energy consumption of FP multipliers. This paper proposes a multiple-precision FP multiplier to efficiently trade the energy consumption with the output quality. The proposed FP multiplier can perform lowprecision multiplication that generates 8−, 14−, 20−, or 26bit mantissa product through an iterative and truncated modified Booth multiplier. Energy saving for lowprecision multiplication is achieved by partially suppressing the computation of mantissa multiplier. In addition, the proposed multiplier allows the bitwidth of mantissa in the multiplicand, multiplier, and output product to be dynamically changed when it performs different FP multiplication operations to further reduce energy consumption. Experimental results show that the proposed multiplier can achieve 59 %, 71 %, 73 %, and 82 % energy saving under 0.1 %, 1 %, 5 %, and 11 % accuracy loss, respectively, for the RGB-to-YUV & YUV-to-RGB conversion when compared to the conventional IEEE single-precision multiplier. In addition, the results also exhibit that the proposed multiplier can obtain more energy reduction than previous multipleprecision iterative FP multipliers.
Bootstrapping a Neural Conversational Agent with Dialogue Self-Play, Crowdsourcing and On-Line Reinforcement Learning
(2018)

End-to-end neural models show great promise towards building conversational agents that are trained from data and on-line experience using supervised and reinforcement learning. However, these models require a large corpus of dialogues to learn effectively. For goal-oriented dialogues, such datasets are expensive to collect and annotate, since each task involves a separate schema and database of entities. Further, the Wizard-of-Oz approach commonly used for dialogue collection does not provide sufficient coverage of salient dialogue flows, which is critical for guaranteeing an acceptable task completion rate in consumer-facing conversational agents. In this paper, we study a recently proposed approach for building an agent for arbitrary tasks by combining dialogue self-play and crowd-sourcing to generate fully-annotated dialogues with diverse and natural utterances. We discuss the advantages of this approach for industry applications of conversational agents, wherein an agent can be rapidly bootstrapped to deploy in front of users and further optimized via interactive learning from actual users of the system.
Characterization and Implementation of Dual-SiC MOSFET Modules for Future Use in Traction Converters
(2015)

Silicon (Si) insulated-gate bipolar transistors are widely used in railway traction converters. In the near future, silicon carbide (SiC) technology will push the limits of switching devices in three directions: higher blocking voltage, higher operating temperature, and higher switching speeds. The first silicon carbide (SiC) MOSFET modules are available on the market and look promising. Although they are still limited in breakdown voltage, these wide-bandgap components should improve traction-chain efficiency. Particularly, a significant reduction in the switching losses is expected which should lead to improvements in power-weight ratios. Nevertheless, because of the high switching speed and the high current levels required by traction applications, the implementation of these new modules is critical. An original method is proposed to compare, in terms of stray inductance, several dc bus-bar designs. To evaluate the potential of these new devices, a first set of measurements, based on a single-pulse test-bench, was obtained. The switching behavior of SiC devices was well understood at turn-off and turn-on. To complete this work, the authors use an opposition method to compare Si-IGBT and SiC-MOSFET modules in voltage source inverter operation. For this purpose, a second test-bench, allowing electrical and thermal measurements, was developed. Experimental results confirm the theoretical loss-calculation of the single-pulse tests and the correct operation of up to three modules directly connected in parallel. This analysis provides guidelines for a full SiC inverter design, and prospects for developments in traction applications are presented.
A High-Speed Mesh of Tactile Sensors Fitting Arbitrary Surfaces
(2010)

A tactile sensor is developed with the aim of covering a robot's entire structure, while reducing wiring requirement and ensuring high-speed response. The sensor detects the center point of load distribution on 2-D surfaces as well as the overall load. There are only four signal wires from the sensor. The sensor response time is nearly constant (within 1 ms) regardless of the number of detection elements, their placements or sensor areas. In this paper, the principles behind the operation of this sensor and the results of experiments using the sensor are described.
A PPG sensor for continuous cuffless blood pressure monitoring with self-adaptive signal processing
(2017)

A new portable PPG-BP device designed for continuously measuring blood pressure (BP) without a cuff is proposed in this study. This continuous and long-time BP monitoring enabled herein by the proposed portable cuffless BP sensor. Towards the aforementioned goal, the sensor is designed capable of detecting in real time, non-invasively and continuously the temporal intravascular blood volume change based on the principle of photoplethysmograph (PPG) for estimating BP. The hardware of the sensor consists mainly of light emitting diodes (LEDs) in wavelengths of 660 nm, a photo detectors (PD), and also signal processing chips to read output signals of the PD. The PD readout circuit includes a PD pre-amplifier, a band-pass filter, a programmable gain amplifier (PGA), a microcontroller unit for calculation and a wireless module for communication. A laptop is also used to display continuous BPs and conducts statistical analysis and displaying results. 27 subjects participated in the experimental validation, in which the obtained BPs are calibrated by and then compared with the results from a commercial blood pressure monitor by OMRON. The resultant signal-to-noise ratio (SNR) is capable of rising more than 15%, correlation coefficient, R2, for systolic blood pressure (SBP) and diastolic blood pressure (DBP) are 0.89 and 0.98, respectively.
How Visualization Layout Relates to Locus of Control and Other Personality Factors
(2013)

Existing research suggests that individual personality differences are correlated with a user's speed and accuracy in solving problems with different types of complex visualization systems. We extend this research by isolating factors in personality traits as well as in the visualizations that could have contributed to the observed correlation. We focus on a personality trait known as "locus of control” (LOC), which represents a person's tendency to see themselves as controlled by or in control of external events. To isolate variables of the visualization design, we control extraneous factors such as color, interaction, and labeling. We conduct a user study with four visualizations that gradually shift from a list metaphor to a containment metaphor and compare the participants' speed, accuracy, and preference with their locus of control and other personality factors. Our findings demonstrate that there is indeed a correlation between the two: participants with an internal locus of control perform more poorly with visualizations that employ a containment metaphor, while those with an external locus of control perform well with such visualizations. These results provide evidence for the externalization theory of visualization. Finally, we propose applications of these findings to adaptive visual analytics and visualization evaluation.
MVC architecture driven restructuring to achieve client-side web page composition
(2016)

This paper presents a restructuring approach to relocating web page composition from servers to browsers for Java web applications. The objective is to reduce redundant manipulation and transfer of code/data that are shared by web pages. The reduction is carried out through a restructuring algorithm, effectively keeping consistency between source and target applications from the perspective of the model-view-controller (MVC) architecture, because the problem requires the target application to preserve the observable behavior of its source application. Case studies show that our restructuring tool can efficiently support the restructuring process.
High speed cascode flyback converter using multilayered coreless printed circuit board (PCB) step-down power transformer
(2011)

In this paper, design and analysis of the high speed isolated cascode flyback converter using multilayered coreless PCB step down power transformer is presented. The converter is tested for the input voltage variation of 60–120V with a nominal DC input voltage of 90V. The designed converter was simulated and tested successfully up to the output power level of 30W within the switching frequency range of 2.6–3.7MHz. The cascode flyback converter is compared with the single switch flyback converter in terms of operating frequency, gate drive power consumption, conduction losses and stresses on MOSFETs. The maximum energy efficiency of the cascode converter is approximately 81% with a significant improvement of about 3–4% compared to single switch flyback converter. The gate drive power consumption which is more dominant compared to conduction losses of the cascode converter using GaN MOSFET is found to be negligible compared to single switch flyback converter.
Optimal integration of energy storage in distribution networks
(2009)

Energy storage, traditionally well established in the form of large scale pumped-hydro systems, is finding increased attraction in medium and smaller scale systems. Such expansion is entirely complementary to the wider uptake of intermittent renewable resources and to distributed generation in general, which are likely to present a whole range of new business opportunities for storage systems and their suppliers. In the paper, by assuming that Distribution System Operator has got the ownership and operation of storage, a new software planning tool for distribution networks able to define the optimal placement, rating and control strategies of distributed storage systems that minimize the overall network cost is proposed. This tool will assist the System Operators in defining the better integration strategies of distributed storage systems in distribution networks and in assessing their potential as an option for a more efficient operation and development of future electricity distribution networks.
ACES: Automatic Compartments for Embedded Systems
(2018)

Securing the rapidly expanding Internet of Things (IoT) is critical. Many of these “things” are vulnerable baremetal embedded systems where the application executes directly on hardware without an operating system. Unfortunately, the integrity of current systems may be compromised by a single vulnerability, as recently shown by Google’s P0 team against Broadcom’s WiFi SoC. We present ACES (Automatic Compartments for Embedded Systems), an LLVM-based compiler that automatically infers and enforces inter-component isolation on bare-metal systems, thus applying the principle of least privileges. ACES takes a developer-specified compartmentalization policy and then automatically creates an instrumented binary that isolates compartments at runtime, while handling the hardware limitations of baremetal embedded devices. We demonstrate ACES’ ability to implement arbitrary compartmentalization policies by implementing three policies and comparing the compartment isolation, runtime overhead, and memory overhead. Our results show that ACES’ compartments can have low runtime overheads (13% on our largest test application), while using 59% less Flash, and 84% less RAM than the Mbed μVisor—the current state-of-theart compartmentalization technique for bare-metal systems. ACES ‘ compartments protect the integrity of privileged data, provide control-flow integrity between compartments, and reduce exposure to ROP attacks by 94.3% compared to μVisor.
On the speedup of single-disk failure recovery in XOR-coded storage systems: Theory and practice
(2012)

Modern storage systems stripe redundant data across multiple disks to provide availability guarantees against disk failures. One form of data redundancy is based on XOR-based erasure codes, which use only XOR operations for encoding and decoding. In addition to providing failure tolerance, a storage system must also provide fast failure recovery to avoid data unavailability. We consider the problem of speeding up the recovery of a single-disk failure for arbitrary XOR-based erasure codes. We address this problem from both theoretical and practical perspectives. We propose a replace recovery algorithm, which uses a hill-climbing technique to search for a fast recovery solution, such that the solution search can be completed within a short time period. We further implement our replace recovery algorithm atop a parallelized architecture to justify its practicality. We experiment our replace recovery algorithm and its parallelized implementation on a networked storage system testbed, and demonstrate that our replace recovery algorithm uses less recovery time than the conventional approach.
Internet of Cloud: Security and Privacy issues
(2018)

The synergy between the cloud and the IoT has emerged largely due to the cloud having attributes which directly benefit the IoT and enable its continued growth. IoT adopting Cloud services has brought new security challenges. In this book chapter, we pursue two main goals: 1) to analyse the different components of Cloud computing and the IoT and 2) to present security and privacy problems that these systems face. We thoroughly investigate current security and privacy preservation solutions that exist in this area, with an eye on the Industrial Internet of Things, discuss open issues and propose future directions.
K-means clustering via principal component analysis
(2004)

Principal component analysis (PCA) is a widely used statistical technique for unsupervised dimension reduction. K-means clustering is a commonly used data clustering for performing unsupervised learning tasks. Here we prove that principal components are the continuous solutions to the discrete cluster membership indicators for K-means clustering. New lower bounds for K-means objective function are derived, which is the total variance minus the eigenvalues of the data covariance matrix. These results indicate that unsupervised dimension reduction is closely related to unsupervised learning. Several implications are discussed. On dimension reduction, the result provides new insights to the observed effectiveness of PCA-based data reductions, beyond the conventional noise-reduction explanation that PCA, via singular value decomposition, provides the best low-dimensional linear approximation of the data. On learning, the result suggests effective techniques for K-means data clustering. DNA gene expression and Internet newsgroups are analyzed to illustrate our results. Experiments indicate that the new bounds are within 0.5-1.5% of the optimal values.
Cartesian K-Means
(2013)

A fundamental limitation of quantization techniques like the k-means clustering algorithm is the storage and run-time cost associated with the large numbers of clusters required to keep quantization errors small and model fidelity high. We develop new models with a compositional parameterization of cluster centers, so representational capacity increases super-linearly in the number of parameters. This allows one to effectively quantize data using billions or trillions of centers. We formulate two such models, Orthogonal k-means and Cartesian k-means. They are closely related to one another, to k-means, to methods for binary hash function optimization like ITQ (Gong and Lazebnik, 2011), and to Product Quantization for vector quantization (Jegou et al., 2011). The models are tested on large-scale ANN retrieval tasks (1M GIST, 1B SIFT features), and on codebook learning for object recognition (CIFAR-10).
Aggregating local descriptors into a compact image representation
(2010)

We address the problem of image search on a very large scale, where three constraints have to be considered jointly: the accuracy of the search, its efficiency, and the memory usage of the representation. We first propose a simple yet efficient way of aggregating local image descriptors into a vector of limited dimension, which can be viewed as a simplification of the Fisher kernel representation. We then show how to jointly optimize the dimension reduction and the indexing algorithm, so that it best preserves the quality of vector comparison. The evaluation shows that our approach significantly outperforms the state of the art: the search accuracy is comparable to the bag-of-features approach for an image representation that fits in 20 bytes. Searching a 10 million image dataset takes about 50ms.
Internet of Things Security Analysis
(2011)

Internet of Things is an up-and-coming information and technology industry, and in such an environment of the concept and the content and the extension of Internet of Things are not very distinctive, the project of Internet of Things which is a piece of small area with small-scale and self-system obtain gratifying achievement and bright future, it can promote the development of Internet of Things in some extent. But there are some serious hidden danger and potential crisis problems. The paper focuses on the application of Internet of Things in the nation and even in the global in the future, analysing the existed security risks of the Internet of Things 's network points, transmission, finally we propose some suggestive solutions due to these problems.
Open Targets: a platform for therapeutic target identification and validation
(2017)

We have designed and developed a data integration and visualization platform that provides evidence about the association of known and potential drug targets with diseases. The platform is designed to support identification and prioritization of biological targets for follow-up. Each drug target is linked to a disease using integrated genome-wide data from a broad range of data sources. The platform provides either a target-centric workflow to identify diseases that may be associated with a specific target, or a disease-centric workflow to identify targets that may be associated with a specific disease. Users can easily transition between these target- and disease-centric workflows. The Open Targets Validation Platform is accessible at https://www.targetvalidation.org.